文献
J-GLOBAL ID:201802261014302599
整理番号:18A1726259
航空宇宙運用複雑性評価のための知識伝達ベース学習フレームワーク【JST・京大機械翻訳】
A knowledge-transfer-based learning framework for airspace operation complexity evaluation
著者 (9件):
Cao Xianbin
(School of Electronics and Information Engineering, Beihang University, Beijing 100191, China)
,
Cao Xianbin
(Key Laboratory of Near Space Information System, Ministry of Industry and Information Technology, Beijing 100191, China)
,
Zhu Xi
(School of Electronics and Information Engineering, Beihang University, Beijing 100191, China)
,
Zhu Xi
(Key Laboratory of Near Space Information System, Ministry of Industry and Information Technology, Beijing 100191, China)
,
Tian Zhencai
(Operation Supervisory Center, Civil Aviation Administration of China, Beijing 100710, China)
,
Chen Jun
(School of Engineering and Materials Science, Queen Mary University of London, London E1 4NS, UK)
,
Wu Dapeng
(Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, United States)
,
Du Wenbo
(School of Electronics and Information Engineering, Beihang University, Beijing 100191, China)
,
Du Wenbo
(Key Laboratory of Near Space Information System, Ministry of Industry and Information Technology, Beijing 100191, China)
資料名:
Transportation Research. Part C. Emerging Technologies
(Transportation Research. Part C. Emerging Technologies)
巻:
95
ページ:
61-81
発行年:
2018年
JST資料番号:
W0534A
ISSN:
0968-090X
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)